Prathmesh Madhu
Prathmesh Madhu, M. Sc.
Academic CV
- Since December, 2018:
Ph.D Researcher at Lehrstuhl für mustererkennung (LME) at Friedrich-Alexander-Universität Erlangen-Nürnberg, - July, 2016 to November, 2018:
Machine Learning Engineer at InFoCusp Innovations Pvt. Ltd. - July, 2014 to May, 2016:
M.Tech in ICT at Dhirubhai Ambani Institute of Information and Communication Technology.
Projects
2019
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ICONOGRAPHICS: Computational Understanding of Iconography and Narration in Visual Cultural Heritage
(FAU Funds)
Term: April 1, 2019 - March 31, 2021The interdisciplinary research project Iconographics is dedicated to innovative possibilities of digital image recognition for the arts and humanities. While computer vision is already often able to identify individual objects or specific artistic styles in images, the project is confronted with the open problem of also opening up the more complex image structures and contexts digitally. On the basis of a close interdisciplinary collaboration between Classical Archaeology, Christian Archaeology, Art History and the Computer Sciences, as well as joint theoretical and methodological reflection, a large number of multi-layered visual works will be analyzed, compared and contextualized. The aim is to make the complex compositional, narrative and semantic structures of these images tangible for computer vision.
Iconography and Narratology are identified as a challenging research questions for all subjects of the project. The iconography will be interpreted in its plot, temporality, and narrative logic. Due to its complex cultural structure; we selected four important scenes:
- The Annunciation of the Lord
- The Adoration of the Magi
- The Baptism of Christ
- Noli me tangere (Do not touch me)
2018
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Automatic Intraoperative Tracking for Workflow and Dose Monitoring in X-Ray-based Minimally Invasive Surgeries
(Third Party Funds Single)
Term: June 1, 2018 - May 31, 2021
Funding source: Bundesministerium für Bildung und Forschung (BMBF)The goal of this project is the investigation of multimodal methods for the evaluation of interventional workflows in the operation room. This topic will be researched in an international project context with partners in Germany and in Brazil (UNISINOS in Porto Alegre). Methods will be developed to analyze the processes in an OR based on signals from body-worn sensors, cameras and other modalities like X-ray images recorded during the surgeries. For data analysis, techniques from the field of computer vision, machine learning and pattern recognition will be applied. The system will be integrated in a way that body-worn sensors developed by Portabiles as well as angiography systems produced by Siemens Healthcare can be included alongside.
Publications
2025
Unpublished Publications
Attention-Guided Erasing for Enhanced Transfer Learning in Breast Abnormality Classification
(2025)
DOI: 10.21203/rs.3.rs-4305449/v1
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Classification of Luminal Subtypes in Full Mammogram Images Using Transfer Learning
(2025)
DOI: 10.48550/arXiv.2301.09282
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2024
Journal Articles
Smelly, dense, and spreaded: The Object Detection for Olfactory References (ODOR) dataset
In: Expert Systems With Applications 255, Part B (2024), Article No.: 124576
ISSN: 0957-4174
DOI: 10.1016/j.eswa.2024.124576
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Conference Contributions
Enhancing downstream classification of breast abnormalities in contrast enhanced spectral mammography using a neighborhood representation loss
SPIE Medical Imaging 2024 (San Diego, February 18, 2024 - February 23, 2024)
In: Weijie Chen, Susan M. Astley (ed.): Medical Imaging 2024: Computer-Aided Diagnosis 2024
DOI: 10.1117/12.3004102
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Attention-guided Erasing
Bildverarbeitung für die Medizin 2024 (Erlangen, March 10, 2024 - March 12, 2024)
In: Andreas Maier, Thomas M. Deserno, Heinz Handels, Klaus Maier-Hein, Christoph Palm, Thomas Tolxdorff (ed.): Bildverarbeitung für die Medizin 2024, Wiesbaden: 2024
DOI: 10.1007/978-3-658-44037-4_8
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2023
Conference Contributions
SniffyArt: The Dataset of Smelling Persons
SUMAC '23: Proceedings of the 5th Workshop on analySis, Understanding and proMotion of heritAge Contents (Ottawa ON, Canada)
In: Proceedings of the 5th Workshop on AnalySis, Understanding and ProMotion of HeritAge Contents 2023
DOI: 10.1145/3607542.3617357
URL: https://arxiv.org/abs/2311.11888
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Thesis
Concepts to Computational Constructs: Advanced Scene Understanding for Heterogeneous Artworks Using Deep Learning (Dissertation, 2023)
URL: https://opus4.kobv.de/opus4-fau/frontdoor/index/index/docId/23213
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2022
Journal Articles
ICC++: Explainable Feature Learning for Art History using Image Compositions
In: Pattern Recognition (2022), p. 109153
ISSN: 0031-3203
DOI: 10.1016/j.patcog.2022.109153
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Enhancing Human Pose Estimation in Ancient Vase Paintings via Perceptually-grounded Style Transfer Learning
In: Journal of Computing and Cultural Heritage (2022)
ISSN: 1556-4673
DOI: 10.1145/3569089
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Conference Contributions
Transfer Learning for Olfactory Object Detection
Digital Humanities 2022 (Tokyo, Japan, Online, July 25, 2022 - July 29, 2022)
In: Alliance of Digital Humanities Organizations (ed.): Digital Humanities 2022 Conference Abstracts 2022
Open Access: https://arxiv.org/abs/2301.09906
URL: https://dh2022.dhii.asia/dh2022bookofabsts.pdf
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ARIN: Adaptive Resampling and Instance Normalization for Robust Blind Inpainting of Dunhuang Cave Paintings
2022 Eleventh International Conference on Image Processing Theory, Tools and Applications (IPTA) (Salzburg, April 19, 2022 - April 22, 2022)
DOI: 10.1109/IPTA54936.2022.9784144
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One-Shot Object Detection in Heterogeneous Artwork Datasets
2022 Eleventh International Conference on Image Processing Theory, Tools and Applications (IPTA) (Salzburg, Austria, April 19, 2022 - April 22, 2022)
DOI: 10.1109/IPTA54936.2022.9784141
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Effect of Random Histogram Equalization on Breast Calcification Analysis Using Deep Learning
German Workshop on Medical Image Computing, 2022
DOI: 10.1007/978-3-658-36932-3_38
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ODOR: The ICPR2022 ODeuropa Challenge on Olfactory Object Recognition
26th International Conference on Pattern Recognition / 8th International Workshop on Image Mining - Theory and Applications (IMTA) (Montreal)
In: 2022 26TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR), NEW YORK: 2022
DOI: 10.1109/ICPR56361.2022.9956542
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2021
Conference Contributions
Analysis of Interventional Workflow Phases based on Image Classification
65th Annual Meeting of the German Association for Medical Informatics, Biometry and Epidemiology (GMDS) (Berlin (online conference), September 6, 2020 - September 9, 2020)
In: 65th Annual Meeting of the German Association for Medical Informatics, Biometry and Epidemiology (GMDS) 2021
DOI: 10.3205/20gmds187
URL: https://www.egms.de/static/en/meetings/gmds2020/20gmds187.shtml
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Abstract: Deep Learning-based Quantification of Pulmonary Hemosiderophages in Cytology Slides
German Workshop on Medical Image Computing, 2021 (Regensburg, March 7, 2021 - March 9, 2021)
In: Christoph Palm, Heinz Handels, Klaus Maier-Hein, Thomas M. Deserno, Andreas Maier, Thomas Tolxdorff (ed.): Informatik aktuell 2021
DOI: 10.1007/978-3-658-33198-6_13
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2020
Journal Articles
Deep Learning-Based Quantification of Pulmonary Hemosiderophages in Cytology Slides
In: Scientific Reports 10 (2020), Article No.: 9795
ISSN: 2045-2322
DOI: 10.1038/s41598-020-65958-2
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Conference Contributions
Understanding Compositional Structures in Art Historical Images Using Pose and Gaze Priors
ECCV 2020 (Glasgow, August 23, 2020 - August 28, 2020)
In: Andrea Vedaldi, Horst Bischof, Thomas Brox, Jan-Michael Frahm (ed.): Computer Vision – ECCV 2020 Workshops. ECCV 2020, Switzerland: 2020
DOI: 10.1007/978-3-030-66096-3_9
URL: https://link.springer.com/chapter/10.1007/978-3-030-66096-3_9
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Computer Vision Understanding of Narrative Strategies on Greek Vases
48th Computer Applications and Quantitative Methods in Archaeology Conference (Oxford, UK, April 14, 2020 - April 17, 2020)
In: Computer Applications and Quantitative Methods in Archaeology 2020
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Deep Learning based Attribute Representation in Ancient Vase Paintings
Digital Humanities 2020 - Intersections/Carrefours (Ottawa, Canada, July 22, 2020 - July 24, 2020)
In: Digital Humanities 2020 - Intersections/Carrefours 2020
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Towards Image Caption Generation for Art Historical Data
URL: https://aidh.kinf.wiai.uni-bamberg.de/02_Gupta_et_al_Towards_Image_Caption_Generation_etc.pdf
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2019
Conference Contributions
Recognizing Characters in Art History Using Deep Learning
SUMAC 2019 - The 1st workshop on Structuring and Understanding of Multimedia heritAge Contents (Nice, October 21, 2019 - October 25, 2019)
In: Recognizing Characters in Art History Using Deep Learning 2019
DOI: 10.1145/3347317.3357242
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Openings
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